During the manufacturing of metal food containers, a number of defects in the flange may exist which should cause the can to be rejected, such as nicks, dents, knockdowns and the like, as well as grease, oil, blistered or nonuniform coatings, and debris. Such flaws or defects are sometimes produced during the manufacturing process and/or as a result of contamination after manufacture, but prior to the filling of the container. Small defects in the flange of a metal container can be especially troublesome. Such defects can be too small to be detected by conventional machine inspection techniques, yet still be large enough to interfere with the proper sealing of the can, thereby permitting leakage or contamination of the contents.
Machine vision is the technology of acquiring or sensing an image of a selected portion of the container through an electronic sensor and determining the existence of any marks or defects in the image and the acceptability of any such marks or defects by use of a vision computer. In typical machine vision technology, a television camera acquires an image and a dedicated vision computer processes and analyzes the image.
While human vision may outperform its automatic equivalent in its sheer ability to analyze very complex, everyday scenes, when it comes to repeated tasks, such as the inspection of aluminum beverage containers over and over again, a human observer understandably tires, loses concentration, and makes mistakes. Machine vision inspection of metal containers is known to provide some important advantages, including sophisticated image processing/analysis, repeatable performance, image acquisition for diagnosis and setup, ability to inspect a variety of containers, and large tolerance in required part placement. Moreover, at conveyor line speeds of up to 2000 containers per minute, each container spends about 30 milliseconds at an inspection station. At those speeds, only a machine vision system is fast enough to reliably, and repeatably, inspect a container in that amount of time.
Machine inspection of glassware is well known. See, for example, U.S. Pat. No. 4,758,084 to Tokumi, et al., U.S. Pat. No. 4,914,289 to Nguyen, et al., and U.S. Pat. No. 4,682,023 to Yoshita. However, machine inspection of metal containers presents unique problems.
First, the containers are inherently opaque, so the inspection system must operate on the light reflected from the metallic surfaces of the selected areas being inspected, as compared to glassware inspection systems which sense or capture light passing through the glassware. Second, some small defects in the flange may be too small to be detected by conventional machine vision techniques, yet because of the way that the container top is attached to the flange, some of those small defects may still be large enough to prevent proper sealing. For example, conventional machine vision techniques can reliably detect defects having a size on the order of 0.040 inch. However, the salmon industry requires detection of 0.014 to 0.020 inch defects. Thus, a need exists for a reliable and economical method of detecting small defects in the flange of a metal container that might otherwise interfere with the proper sealing of the container.